Next-Day Workout Retention

PandasHardSenior level~10 min

Problem

A fitness app records each workout session a member logs in a DataFrame `workout_log` (`workout_log.csv`).

There may be several rows per member. Each row records one day on which the member logged a workout. A member's signup date is the earliest `log_date` they have.

Write a function that reports, for each signup date, how many members signed up on that date (`signups`) and the fraction of those members who logged another workout on the very next day (`next_day_rate`), rounded to 2 decimal places. Return columns `signup_date`, `signups`, and `next_day_rate` in any order.

Input data

Example rows — the live problem includes the full dataset.

workout_log

member_id	device_id	log_date	minutes
1	2	2022-03-01	45
1	2	2022-03-02	30
2	3	2022-04-10	20
3	1	2022-03-01	0
3	4	2022-06-15	50

Expected output

Your answer should return 3 rows with the columns signup_date, signups, next_day_rate.

Starter code (Pandas (Python))

import pandas as pd

def next_day_retention(workout_log: pd.DataFrame) -> pd.DataFrame:
    # Your code here
    return workout_log

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